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Reversible quantum circuits are constructed using different types and numbers of quantum gates. Optimizing the number of gates to be used while creating quantum circuits reduces the cost and complexity. It is important to know the number of inputs, outputs, and gates for obtaining and optimizing state tables in reversible quantum circuits. In addition, these parameters are also used to detect faults that may occur in quantum circuits. There is a lack of determination of the input, output, and gate numbers for quantum circuits in the literature. In addition, a limited number of standard quantum circuits are used to test the applications made in the literature. It has been determined that there are very few datasets that can be used in this context. Elimination of these deficiencies in the literature constitutes the aim of our study, and the proposed method constitutes the originality of our study. In this study, the number of gates and inputs were determined by using Yolo (You Only Look Once) based methods. A large dataset consisting of CNOT, Feynman, and Toffoli gates was created using the "MATLAB" and "RCViewer+" programs. In this study, a total of 5000 quantum circuits with 1-8 gate numbers and 3-7 input numbers were created. Gates and inputs are labeled on the obtained datasets. YoloV4, YoloV7, and YoloV7x methods were applied to the tagged datasets with a training and testing ratio of 80:20. 87.1%, 89.7% and 89.3% mAP were calculated for the YoloV4, YoloV7 and YoloV7x methods, respectively. The proposed method was run for 2800 iterations and the best result was obtained with the YoloV7 algorithm. [ABSTRACT FROM AUTHOR]